Man Luo
About
I am currently an Senior ML Scientist at Abridge. My research includes Multimodal and language models post-training, Multimodal Retrieval and Generation, Synthetic Data Pipelines, Computer Use Agents, and Multimodal Applications in Healthcare. More details:
- Knowledge Retrieval: How can we effectively retrieve and utilize external knowledge to not only enhance comprehension but also mitigate hallucination?
- Generalization: Designing models that can seamlessly adapt and perform across various tasks and domains without explicit training.
- Multimodal Understanding: Delving into the integration of textual, visual, and other modalities to bolster machine comprehension and response capabilities.
- Biomedical/healthcare application and innovation: Evaluate and innovate the LLMs to solve biomedical and healthcare challenges, such as long sequence processing, noisy data mitigation, data imbalance rectification, and enhancing interpretability.
Previously, I was a AI research scientist at Intel Lab and research fellow at Mayo Clinic, AZ.I earned my doctoral degree in 2023 from Arizona State University under the esteemed supervision of Dr. Chitta Baral. I am also privileged to collaborate with amazing industry researchers from Salesforce, Meta and Google during my internship.
Publications
In-BoXBART: Get Instructions into Biomedical Multi-Task Learning
Mihir Parmar, Swaroop Mishra, Mirali Purohit, Man Luo, M. Hassan Murad, Chitta Baral
NAACL 2022 Finding
[Paper]
[Model in Huggingface]
In-context Learning with Retrieved Demonstrations for Language Models: A Survey
Man Luo, Xin Xu, Yue Liu, Panupong Pasupat, Mehran Kazemi
TACL 2024
[Paper]
Improving Biomedical Information Retrieval with Neural Retrievers
Man Luo, Arindam Mitra, Tejas Gokhale, Chitta Baral
AAAI 2022
[Paper]
'Just because you are right, doesn't mean I am wrong': Overcoming a bottleneck in development and evaluation of Open-Ended VQA tasks
Man Luo, Shailaja Keyur Sampat, Riley Tallman, Yankai Zeng, Manuha Vancha, Akarshan Sajja, Chitta Baral
EACL 2021
[Paper]
[Code]
Dr. ICL: Demonstration-Retrieved In-context Learning
Man Luo, Xin Xu, Zhuyun Dai, Panupong Pasupat, Mehran Kazemi, Chitta Baral, Vaiva Imbrasaite, Vincent Y Zhao
Data Intelligence Journal 2024
[Paper]